The 2015 AMMCS-CAIMS Congress

Interdisciplinary AMMCS Conference Series

Waterloo, Ontario, Canada | June 7-12, 2015

AMMCS-CAIMS 2015 Plenary Talk

An Information Theoretic Approach to Computational Modelling in Engineering and the Sciences

Nicholas Zabaras (University of Warwick)

Predictive modelling and design of materials gives rise to unique mathematical and computational challenges including (i) Modelling of hierarchical random heterogeneous material structures; (ii) Propagating uncertainties in a quantifiable manner across spatial and temporal length scales (stochastic coarse graining); (iii) Addressing the curse of stochastic dimensionality; (iv) Addressing the phenomenology typical of most materials science models; (v) Modelling failure and rare events in random media; and many more.
We will advocate an information theoretic approach to address some of these challenges. In particular, we will discuss data-driven models of material structure, forward uncertainty propagation in high dimensions using limited data, variational approaches to stochastic coarse graining, and quantifying epistemic uncertainty when using surrogate models. We will finally address the importance of using probabilistic graphical models for predictive modelling of multiscale and multiphysics problems.
With synergistic developments in materials physics, computational mathematics/statistics, and machine learning there is potential for developing data-driven materials models that allow us to understand where observable variabilities in properties arise and provide means to control them for accelerated materials design.
Nicholas Zabaras received his PhD at Cornell University (1987) in the area of Theoretical and Applied Mechanics. Upon graduation he joined the faculty of Engineering at the University of Minnesota. In 1991 he returned to Cornell as a faculty member of the Sibley School of Mechanical and Aerospace Engineering where he was also member of various other academic fields including Applied Mathematics, Materials Science and Engineering and Computational Science and Engineering. He was the founding director of the Materials Process and Design Laboratory that integrated materials modelling and design with innovative mathematical approaches including inverse problems, uncertainty quantification, robust design, and scientific computing. In the summer of 2014 he joined the University of Warwick to establish and lead the Warwick Centre for Predictive Modelling. WCPM is a university wide initiative across many colleges and departments with emphasis on the integration of computational mathematics, computational statistics and scientific computing to address modelling and design of complex systems in the presence of uncertainties. He has received several awards including a Presidential Young Investigator Award in 1991. He is Fellow and member of various societies. In 2014, Prof. Zabaras was appointed as Hans Fisher Senior Fellow at the Institute of Advanced Study at the Technische Universität München. The same year he received the Royal Society’s Wolfson Research Merit Award for his work on predictive modelling. He is currently an Associate Editor of the Journal of Computational Physics and the Editor in Chief of the International Journal for Uncertainty Quantification.